This is a proposal to continue a successful research training program in the genetic epidemiology and statistical analysis of psychiatric and other complex diseases. The field of psychiatric genetics is changing rapidly, and successful investigators must be competent in a broad array of techniques, must be able to speak the languages of fields outside their own, and must be able to collaborate effectively with scientists in other fields. The program trains postdoctoral (M.D., Ph.D., and Dr.P.H.) and predoctoral Fellows. Training has both (a) didactic and (b) research components. (a) The didactic component is further broken down into an academic program and a series of practical laboratory rotations. The academic program includes a series of academic courses in human genetics, epidemiology, statistical genetics, computer simulations, research communication skills, and responsible conduct of research. The laboratory rotations take place in a number of laboratories at Columbia University, where a rich and broad variety of genetic studies are being carried out. (b) In the research component each Fellow works closely with a Preceptor on an independent research project of the Fellow's choosing;the Fellow prepares a clearly written research proposal, carries out the proposal, prepares an oral description of the study and its results, and prepares a publishable manuscript based on the completed study. At the end of training, Fellows understand: the biological underpinnings of genetic influences on disease risk;how to formulate testable hypotheses in human genetics and design studies to test those hypotheses;the critical importance of phenotype definition;how to design data collection strategies for genetic studies;the factors that go into selecting appropriate samples;issues of responsible conduct of research and Good Clinical Practice;the mathematical underpinnings of genetic analysis, including familial aggregation studies, twin studies, and segregation, linkage, and association analysis;laboratory techniques such as genotyping and sequencing, extracting DMA from blood, PCR, etc.;proper data management of genetic and clinical data through the use of a data base management system;how to use current genetic analysis programs, to interpret the results, and to test and evaluate new methods of genetic analysis as they become available;and microarray technology and other current molecular-biological techniques.